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Sinkron : Jurnal dan Penelitian Teknik Informatika
Published by Politeknik Ganesha Medan
ISSN : 2541044X     EISSN : 25412019     DOI : 10.33395/sinkron.v8i3.12656
Core Subject : Science,
Computer Science & IT
Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial Neural Network 14. Fuzzy Logic 15. Robotic
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 1,196 Documents
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Analysis And Design of Mobile Applications For Make-Up Artist Services (Halomua) With The Design Thinking Framework Fajri, Fathorazi Nur; Rizal, Fathur; Yaqin, Moh. Ainol; Purwanto, Zendi Ari
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12483

Abstract

Designing an application user interface design is an important part of creating an attractive application. However, there are several problems such as lack of attention to detail, failure to identify and solve customer problems, and poor planning or organization. The design thinking method performs stages ranging from empathize, define, ideate, and prototype, to usability testing to reduce these problems. At the empathize stage, data is obtained through interviews with MUAs and online questionnaires that have been filled out by respondents. At the define stage, a profile picture of each respondent along with their problems and goals was created. At the idea stage, feature mapping, information architecture, low fidelity wireframe, medium fidelity wireframe, and user flow are made so that it can facilitate users in operating the tasks designed in the application. The prototype stage is to create a flowchart design for each case so that users can find out how the application can run properly. The results of usability and user satisfaction are measured using the System Usability Scale (SUS). The SUS average value of 85.2 is obtained, which means that the value of the UI design results is included in category B with an "Excellent" status.
A Mathematical Approach to Dampening Sea Waves Using Submerged Permeable Breakwater Marpaung, J.L.; Tulus; Gultom, Parapat
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12489

Abstract

A wave is an energy that can propagate with a medium; the propagation of a wave moves with respect to time by carrying energy that moves with velocity per unit of time. Sea waves are one of the propagating wave problems that are broken down to produce wave propagation with a relatively inhomogeneous minimum amplitude and speed of sea waves, which have their own difficulties in solving them numerically. This study aims to analyze the stability of wave propagation on submerged breakwaters. This research will approximate the finite discretization of the breakwater domain and then combine it with the Finite Element Method to determine the moving elements of the velocity of fluid flow through a porous submerged breakwater. The research has explained the equation of the inflated wave and the simulated representation displayed on the wave breakdown process, the point that becomes the center of the waves breakdown will give a focused red color indicator meaning there is a change in momentum and potential energy that occurs and then changes the colour of the post-flattering of the sea wave so that the sinking wave breaker is a method to obtain the minimum speed and amplitude values that can be used for coastal engineering.
Leveraging Technology for MSME Development: A Case Study of the Sistem Informasi Hasil Desa (SIHASA) V2 in Banyumas Regency Prabowo, Wahyu Adi; Putri, Tiara Pebriana; Himawan , Zidan Yazid
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12493

Abstract

Banyumas Regency in Central Java Province comprises 27 districts and 331 villages, showcasing its vast geographical coverage. Over three years, from 2006 to 2009, the region witnessed a notable increase in small businesses, rising from 643 to 717 establishments. Despite this growth, MSMEs in Banyumas face a prevalent challenge of inadequate information dissemination for effectively promoting their products. To tackle this issue, a proposed solution is the Village Results Information System (SIHASA) V2 website. This website supports village communities, MSMEs, and governments in managing their respective activities and operations. To expedite the creation of the system, the Rapid Application Development (RAD) method is employed, encompassing essential stages such as project requirement determination, prototype creation, development processes, and gathering feedback. Furthermore, to ensure an efficient system design, the implementation of Unified Modeling Language (UML) is integrated, incorporating crucial components like Use Case Diagrams and Class Diagrams. This meticulous design approach guarantees that the system effectively caters to the community's diverse needs, specifically benefiting the village community in Banyumas Regency in terms of managing village products and facilitating efficient MSME operations. The outcomes of this research endeavor hold significant promise for the community, providing practical tools and resources to enhance their livelihoods and contribute to the overall development of the Banyumas Regency.
Digital Forensic Investigates Sexual Harassment on Telegram using Naïve Bayes Apriyani, Meyti Eka; Maskuri, Rahmad Alfian; Ratsanjani, Muhammad Hasyim; Pramudhita, Agung Nugroho; Rawansyah, Rawansyah
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12514

Abstract

The widespread use of Telegram in Indonesia has had both positive and negative effects. While the app offers strong security features, it has also become a platform for digital crimes, including sexual harassment. This study aims to address the need for effective forensic analysis and classification methods by employing the National Institute of Justice (NIJ) methodology and Naïve Bayes classifier to analyze conversations on Telegram. The research evaluates the performance of digital forensic tools and the effectiveness of the Naïve Bayes method in identifying instances of sexual harassment conversation. The data analyzed is about conversations on the telegram application that contain sexual harassment. Data collection involves extracting relevant conversations and subjecting them to forensic analysis using MOBIL edit Forensic Express and FTK Imager. Based on the test results, the naïve Bayes algorithm can be used to classify conversations into positive and negative about sexual harassment. The value obtained from naïve Bayes testing is the accuracy value of 91.3%, Precision 100%, and Recall 90%.
The Implementation of Support Vector Machine Method with Genetic Algorithm in Predicting Energy Consumption for Reinforced Concrete Buildings Asep Syaputra
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.12516

Abstract

Accurate information on energy consumption is crucial for measuring energy efficiency and savings in buildings. It refers to the energy needed to power a building at a specific time. Energy savings can reduce costs and environmental impact by lowering greenhouse gas emissions. Obtaining precise energy consumption data is essential for all parties involved in building planning, construction, and management. Over the past decades, global energy consumption in buildings has consistently increased, with HVAC systems being a significant contributor. To tackle this problem, research developed a support vector machine model with genetic algorithms to accurately predict energy consumption in buildings. Two models were tested: a standard support vector machine and a genetic algorithm-integrated support vector machine. The test results revealed that the support vector machine model achieved an RMSE value of 2.6. Additionally, the genetic algorithm optimized the parameter C and selected the most relevant predictor variables, reducing the RMSE to 1.7 and utilizing only 3 predictor variables. In the subsequent stage, parameter optimization and function selection were performed to achieve an improved RMSE value of 1.537. This research aims to enhance energy consumption prediction for reinforced concrete buildings by combining SVM and Genetic Algorithm. SVM serves as the primary prediction model, while the Genetic Algorithm is employed to determine optimal SVM parameters and relevant features. Recent studies have demonstrated that this combination yields more accurate predictions compared to standard methods. It enables more efficient energy planning, reduced operational costs, and optimized resource utilization in reinforced concrete buildings. However, it's worth noting that this implementation may require substantial processing and resource utilization, depending on the dataset's size and complexity.
Machine Learning to Identify Monkey Pox Disease Aldi, Febri; Nozomi, Irohito; Sentosa, Rio Bayu; Junaidi, Ahmad
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12524

Abstract

In May 2022, it has received by WHO reports from non-endemic countries on cases of monkey pox disease. Monkey pox is a rare zoonotic disease caused by infection with the monkeypox virus that belongs to the genus orthopoxvirus and the family poxviridae, and also the variola virus. This study aims to classify patients who have contracted the monkey pox virus. We modeled an analysis of monkey pox disease and conducted comparisons utilizing a dataset from Kaggle consisting of a CSV file with records for 25,000 patients. The monkey pox dataset was analyzed using the correlation coefficient and the number of target variables. Machine learning (ML) methods are used for classification by utilizing the K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting (GB) algorithms. This study resulted in the highest classifier Gradient Boosting (GB) algorithm with an accuracy value of 71%. then the accuracy obtained by Support Vector Machine (SVM) is 69%, Random Forest (RF) accuracy is 68%, and finally K-Nearest Neighbor (KNN) obtains 63% accuracy. This ML method is expected to analyze monkey pox disease so that it helps the country and government, especially the health field in assessing, identifying, and being able to take appropriate action against monkey pox disease.
Redesigning the Colega Application Interface and Interaction Using the Learner-Centered Design Method Aufar, Kasyfi Zulkaisi; Dian Martha, Ati Suci; Hadikusuma, Aristyo
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12529

Abstract

In the rapid development of technology, almost all activities are carried out online, activities become timeless so that many students have difficulty in managing time between lectures and other activities. So that students must be able to organize their activity schedule, record tasks and activities that must be completed. One of the efforts that can be made is to use colega products which are technology products to remind activities. The purpose of this research is to redesign the Colega mobile application interface that is suitable and easy to use based on student needs to increase the level of usability with the learner-centered design method., this method is a design process that focuses on the needs of learner, by performing 5 stages, namely Specify the context of use, Specify user requirements, Product design solution, and Evaluate against user requirements. The product developed using this method, the principle of this method is a collaboration that allows learner to develop, test, and analyze their ideas for the product to be made. Interface design and interaction testing using the System Usability Scale. the results of usability testing on the interface obtained a value of 60.62 to 78.12. With the test results obtained an increase in value in the usability aspect. So it can be concluded that the usability value falls into the good and acceptable category.
Sentiment Analysis of Shopee Food Application User Satisfaction Using the C4.5 Decision Tree Method Fersellia, Fersellia; Utami, Ema; Yaqin, Ainul
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12531

Abstract

Sentiment analysis on public opinion regarding the shopee food application is an interesting topic in the context of evaluating service quality in the shopee food application. In this digital era, user opinion has a very important role in shaping public perception of the application. Therefore, sentiment analysis is needed to understand user opinion about the shopee food application. This study uses Decision Tree C4.5 to analyze public sentiment on the use of the Shopee Food application on Twitter users. However, beforehand it is necessary to overcome the problem of data imbalance which is common in datasets, where the number of positive, negative, and neutral sentiments is not balanced. To overcome this problem, three different techniques are used, namely SMOTE, undersampling, and a combination of oversampling and undersampling. The results of this study indicate that the SMOTE technique provides better results in overcoming data imbalances and increasing prediction accuracy. With an accuracy of 0.88. the SMOTE technique can provide more accurate sentiment predictions than the undersampling technique and the combination of oversampling and undersampling. This is because SMOTE can synthetically expand the number of minority samples, thereby preventing the loss of information and maintaining variation in the dataset. In conclusion, sentiment analysis on the Shopee Food application on Google Play using the Decision Tree C4.5 algorithm and the SMOTE technique can overcome data imbalances with a prediction accuracy of 0.88. This technique is more efficient than the undersampling technique and the combination of oversampling and undersampling. These results can provide developers with valuable insights to improve app quality and user satisfaction.
Direct Search Techniques for Mixed Stochastic Nonlinear Programming Model Tanjung, Ilyas; Mawengkang, Herman; Sawaluddin, Sawaluddin
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12542

Abstract

Stochastic programming is a methodology utilized for the purpose of achieving optimal planning and decision-making outcomes when faced with uncertain data. The subject of investigation pertains to a stochastic optimization problem wherein the results of stochastic data are not disclosed during runtime, and the optimization of the decision does not necessitate foresight into forthcoming outcomes. This establishes a strong correlation with the imperative need for immediate optimization in uncertain data settings, enabling effective decision-making in the present moment. The present study introduces a novel methodology for achieving global optimization of the model for nonlinear mixed-stochastic programming problem. The present study centers on stochastic problems that are two-staged and entail non-linearities in both the objective function and constraints. The first stage variables are discrete in nature, whereas the second stage variables are a combination of continuous and mixed types. Scenario-based representations are utilized for formulating problems. The fundamental approach to address the non-linear mixed-stochastic programming problem involves converting the model into a deterministic non-linear mixed-count program that is equivalent in form. The feasibility of this proposition stems from the discrete distribution assumption of uncertainty, which can be represented by a limited set of scenarios. The magnitude of the model size will increase significantly due to the quantity of scenarios and time horizons involved. The utilization of filtered probability space in conjunction with data mining techniques will be employed for the purpose of scenario generation. The methodology employed for addressing nonlinear mixed-integer programming problems of significant scale involves elevating the value of a non-basic variable beyond its boundaries in order to compel a basis variable to attain a cumulative value. Subsequently, the problem is simplified by maintaining a constant count variable and modifying it incrementally in discrete intervals to achieve an optimal solution at a global level.
FREQUENCY ANALYSIS OF DELI RIVER FLOOD DISTRIBUTION PLAN USING THE GUMBEL PROBABILITY DISTRIBUTION METHOD Agustin, Uni; Siregar, Machrani Adi Putri
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12543

Abstract

The Deli river basin is one of the rivers in North Sumatra Province which is in Medan City with an area of ​​394.88 km2 and a length of 166.01 km. Medan Maimun District which has an area of ​​2.98 km2 and a population density of 16,520 people/km2. Medan Mimun sub-district is one of the flood-prone areas which is drained by the Deli River. The cause of the flooding that occurred in Medan Maimun District was high rainfall so that the river flow rate increased and drainage was poor. So that the problem of flooding in the Deli river watershed, Medan Maimun sub-district, can hamper community activities, these floods can also harm and endanger the community. The flood discharge plan for each repeat period where the variable used is the maximum daily rainfall for 10 years From 2013-2022 which is sourced from the BMKG Deli Serdang. In this study using frequency analysis and then proceed with the Gumbel Probability Distribution method, Normal Distribution Log Person Type III. The result of this study with hydrological data and distribution test, the suitable method for analyzing the planned flood discharge in the Deli River is Log Person Type III that it can be flood discharge for a 2 year retention period is 12.7684672 m3/sec, 5 year return period is 12.56275855 m3/sec, 10 year return period is 15.91400029 m3/sec, 25 year return period is 16.87871678 m3/sec, 50 year return period is 17.43836748 m3/sec and a 100 year return period is 17.89619614 m3/sec. Keywords: Rainfall, Deli River, Planned Flood Discharge

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